Orang Asli Communities as Catalysts of Ai-Driven Knowledge Innovation in Malaysia: A Human-Centred Framework for Inclusive Research Incubation

Abstract

The rapid expansion of artificial intelligence (AI) in research and innovation ecosystems has largely been driven by technocentric paradigms that marginalise indigenous knowledge systems, particularly within developing contexts such as Malaysia. This conceptual paper addresses this gap by proposing a human-centred framework that positions Orang Asli communities as active catalysts of AI-driven knowledge innovation and inclusive research incubation. Drawing on interdisciplinary literature across human-centred AI, indigenous epistemology, innovation ecosystem theory and decolonial perspectives, the study synthesises a novel framework—the Human-Centred Indigenous AI Knowledge Incubation (HCI-AIKI) Model. The framework conceptualises the dynamic interaction between indigenous knowledge systems, human-centred AI, enabling policy ecosystems, and knowledge co-creation processes in generating inclusive and sustainable innovation outcomes. It advances the argument that AI should function as an assistive and culturally responsive tool that enhances, rather than replaces, community-based knowledge practices. The proposed model contributes theoretically by integrating relational epistemologies with AI-driven innovation, thereby extending existing human-centred AI discourse into Orang Asli contexts. Practically, it offers strategic insights for policymakers, researchers and institutions in Malaysia to develop inclusive AI ecosystems that empower Orang Asli communities, reduce epistemic inequality and foster sustainable knowledge incubation aligned with national digital transformation goals.